Context-aware Pervasive Applications Research Articles

A service-oriented edge platform for cyber-physical systems

The purpose of this paper is to present an edge pervasive platform supporting the development, deployment and management of flexible, context-aware pervasive applications. This platform, named iCasa, is built on top of the OSGi/iPOJO service-oriented component model. It includes an autonomic context module connected to the physical environment and providing information as a dynamic set of services. This context is dynamic in order to reflect the changing nature of the execution environment but also to deal with applications evolving needs. ICasa also comes with an Eclipse-base development environment including a source code editor, build automation tools, automated deployment facilities, and a smart home configurator and simulator. ICasa has been validated on a variety of applications, mostly in collaboration with Orange Telecom company and Schneider Electric. It is available on the Internet (self-star.net) and is heavily used today for teaching purposes, in addition to industrial developments.

Typed context awareness Ambient Calculus for pervasive applications

Abstract The idea of pervasive computing is that information processing will become part of everyday life, and will be available everywhere, making computing so natural to the point of being invisible in the ambient. An important concept that arises with pervasive computing is context awareness . Context is any information that can be used to characterize an entity. Based on contextual information, applications can dynamically adapt themselves to the environments in which they operate. The Calculus of Context-aware Ambients (CCA) is an untyped formal language used to describe mobile and context-aware pervasive applications. The CCA extends the Ambient Calculus by providing new features, such as context-guarded action and process abstraction, allowing to model contexts and context-aware computations. In this work, we define a type system for the CCA, called CCA T , with the focus in the communication between processes and in the correct use of process abstraction and contexts, extending previous works on the definition of type systems for mobile computing. Moreover, we prove that the proposed type system has the subject reduction property (or type preservation). We also model a hospital scenario using CCA T to demonstrate the use of the proposed type system.

GreenLoc: Energy Efficient Wifi-Based Indoor Localization

User-localization and positioning systems have been a core challenge in the domain of context-aware pervasive systems and applications. GPS has been the de-facto standard for outdoor localization; however, geo-satellite signals upon which GPS rely, are inaccurate in indoor environments. Therefore, various indoor localization techniques based on triangulation, scene analysis, or proximity, have been introduced. The most prominent technologies over which these techniques are applied include WiFi, Bluetooth, RFID, Infrared, and UWB. Due to the ubiquitous deployment of access points, WiFi-based localization via triangulation has emerged to be among the most prominent indoor positioning solutions. A major deployment obstacle for such systems, however, is the high-energy consumption rates of Wifi adapters in mobile devices where energy is the most valuable resource. We propose GreenLoc, an indoor green localization system that exploits sensors prevalent in today's smart-phones in order to dynamically adapt the frequency of location updates required. Significant energy gains can, therefore, be acquired when users are not mobile. For example, accelerometers can aid in detecting different user states such as walking, running or stopping. Based on these states, mobile devices can dynamically decide upon the appropriate update frequency. We accommodate various motion speeds by estimating the velocity of the device using the latest two location coordinates, and the time interval between these two-recorded locations. We have taken the first steps towards implementing GreenLoc, based on the infamous Ekahau system. We have also conducted preliminary tests utilizing the accelerometer, gravity, gyroscope, and light sensors residing on the HTC Nexus One and IPhone4 smart-phones. To further save energy in typical indoor environments, such as malls, schools, and airports, GreenLoc exploits people's proximity when moving in groups. Devices within short-range of each other do not necessarily require that they each be individually tracked. Therefore, GreenLoc detects and clusters users moving together and elects a reference node (RN) based on device energy levels and needs. The elected RN will then be tracked via triangulation while other nodes in the group will be tracked based on the RN's location using Bluetooth. Our initial analysis demonstrates very promising results with this system.

Aspect-oriented design and implementation of context-aware pervasive applications

Pervasive applications must be aware of the contexts where they are executed. These contexts may vary greatly and change quickly. Two main problems are associated with this issue: (1) context-awareness is a crosscutting concern that cannot be well-encapsulated in a single module using traditional technologies, thus hindering software maintenance and reusability; and (2) reasoning about application design correctness can be complex due to the number and diversity of potential contexts where a pervasive application could be executed. In order to overcome these problems, we present a process for the design and implementation of context-aware pervasive applications that uses aspect-orientation and executable modelling in order to overcome these shortcomings. Aspect-oriented techniques contribute to the encapsulation of crosscutting concerns, such as context-awareness, into well-localized modules. Executable modelling helps engineers to reason about application design by executing the design models in different contexts and situations. Pervasive applications are modelled using the aspect-oriented executable modelling UML 2.0 profile, executed at the modelling level for testing purposes, and then mapped into an aspect-oriented middleware platform for pervasive applications. This process is illustrated using a location-aware intelligent transportation system consisting of a set of cooperating sentient vehicles.